ML Biomarker Analysis

Run individual algorithms, compare all 5 simultaneously, or upload your CSV cohort. Stacking ensemble (Random Forest + XGBoost + SVM + ElasticNet + LightGBM) delivers thesis-reported AUC 0.913.

Run ML Algorithms

Custom Data Upload

Upload your own multi-omic cohort CSV or run the demo pipeline.

Upload Your Data

Upload a CSV with columns prefixed by expr_, mut_, meth_, cnv_, or mir_ for feature detection.

Run Demo Analysis

Try the ML pipeline on 500 TCGA samples with 20,531 features across mRNA, miRNA, methylation, and CNV.